Job Description
Join Nexus Quantum Labs at the forefront of technological evolution as we pioneer the 2026 Quantum Computing Initiative. We seek a visionary Research Scientist to develop groundbreaking quantum algorithms and architectures that will redefine computational paradigms. Our state-of-the-art facility in San Francisco offers unparalleled resources for innovation, including access to 128-qubit processors and dedicated AI/ML integration labs. This role is pivotal in transforming theoretical quantum mechanics into practical solutions for cryptography, optimization, and machine learning.
We foster a culture of intellectual curiosity where your expertise in quantum mechanics will directly impact real-world applications. As part of our cross-functional teams, you'll collaborate with Nobel laureates, AI specialists, and industry disruptors to solve humanity's most complex challenges. Your work will contribute to patents, peer-reviewed publications, and next-generation quantum ecosystems.
Responsibilities
- Design and implement novel quantum algorithms for optimization problems and machine learning applications
- Lead research on quantum error correction techniques to achieve fault-tolerant computing
- Develop hybrid quantum-classical frameworks for practical enterprise solutions
- Collaborate with hardware engineers to prototype and validate quantum circuit architectures
- Author high-impact research papers and secure intellectual property protection
- Mentor junior researchers and present findings at international conferences
- Drive partnerships with academic institutions and government quantum programs
Qualifications
- PhD in Quantum Physics, Computer Science, or related field with 3+ years industry experience
- Expertise in quantum programming languages (Q#, Quil, or Qiskit) and simulation frameworks
- Proven track record of publishing in top-tier journals (Nature, Science, etc.)
- Deep understanding of quantum algorithms (Shor's, Grover's, VQE, etc.)
- Proficiency in Python/C++ with experience in quantum machine learning libraries
- Familiarity with quantum hardware architectures (superconducting, trapped ions, photonic)
- Experience with cloud quantum platforms (IBM Quantum, Amazon Braket, Azure Quantum)